A Constrained Mechanism for Procedural Learning
نویسنده
چکیده
The p r o b l e m s t u d i e d i s t h a t o f l e a r n i n g p r o b l e m s o l v i n g h e u r i s t i c s b y d o i n g . The pu rpose i s t o e x p l o r e t h e l e a r n i n g b e h a v i o r o f a h i g h l y c o n s t r a i n e d mechan ism. The c o n s t r a i n t s a r e choosen o n t h e b a s i s o f D s y c h o l o g i c a l c o n s i d e r a t i o n s . Computer r u n s show t h a t t h e c o n s t r a i n t s d o n o t p r e v e n t s u c c e s s f u l l e a r n i n g . T h e l e a r n i n g s t y l e o f t h e p rog ram t u r n s o u t t o b e a f u n c t i o n o f t h e s t r u c t u r e o f t h e p r o b l e m s p a c e . I HEURISTICS LEARNING The t a s k s t u d i e d i n t h i s paper i s t h a t o f d i s c o v e r i n g p r o b l e m s o l v i n g h e u r i s t i c s b y d o i n g . We p resuppose a t a s k i n d e p e n d e n t , weak p r o b l e m s o l v e r w h i c h can t a k e a p r o b l e m space and a p r o b l e m a s i n o u t , and s e a r c h f o r t h e s o l u t i o n t o t h e l a t t e r . We add a s e t o f l e a r n i n g mechanisms w h i c h s p e c i f y how t h e i n f o r m a t i o n g e n e r a t e d d u r i n g s e a r c h s h o u l d b e encoded f o r f u t u r e u s e . The t a s k o f t h e sys tem i s t o c o n s t r u c t a s t r a t e g y f o r s e a r c h i n g a p r o b l e m space on t h e b a s i s o f r e p e a t e d p r o b l e m s o l v i n g t r i a l s i n t h a t s p a c e . Systems o f t h i s k i n d have been d e s c r i b e d by Anza i & Simon ( 1 9 7 9 ) , by L a n g l e v ( 1 9 8 ? ) , by O h l s s o n ( 1 9 8 2 ; 1983), a s w e l l a s b y o t h e r s . They w i l l h e r e b e c a l l e d h e u r i s t i c s l e a r n e r s . The pu rpose o f t h e work r e p o r t e d he re i s n o t t o c o n s t r u c t t h e most i n t e l l i g e n t l e a r n i n g sys tem w h i c h t h e s t a t e o f t h e a r t a l l o w s , b u t t o s t u d y how a p a r t i c u l a r s e t o f c o n s t r a i n t s on an i n f o r m a t i o n p r o c e s s i n g sys tem a f f e c t s i t s l e a r n i n g b e h a v i o r . The c o n s t r a i n t s chosen f o r s t u d y a r e based o n p s y c h o l o g i c a l c o n s i d e r a t i o n s , a l t h o u g h n o d e t a i l e d c o m p a r i s o n between t h e Drogram and human b e h a v i o r w i l l b e made i n t h i s p a p e r . II THE UNIVERSAL PUZZLE LEARNER A n e a r l i e r v e r s i o n o f t h e U n i v e r s a l P u z z l e L e a r n e r (UPL) p rogram has been d e s c r i b e d i n O h l s s o n ( 1 9 8 2 ; 1 9 8 3 ) . The t h i r d and c u r r e n t v e r s i o n c o n s i s t s o f t h r e e l a y e r s : t h e i m p l e m e n t a t i o n l a n g u a g e , t h e p rob lem s o l v e r , and t h e l e a r n i n g mechan isms . A . I m p l e m e n t a t i o n Language UPL i s w r i t t e n i n PSS, a n e o c l a s s i c a l p r o d u c t i o n sys tem language ( O h l s s o n , 1979 ) . I t a l l o w s t h e u s e r t o o r g a n i z e p r o d u c t i o n memory i n t o n o d e s , each node c o n t a i n i n g one o r more p r o d u c t i o n s . When PSS i s " i n " a node , i t w i l l t r y t o f i r e a p r o d u c t i o n f r om t h a t node b e f o r e i t c o n s i d e s p r o d u c t i o n s f r om o t h e r n o d e s . C o n t r o l can be t r a n s f e r r e d f r o m one node to a n o t h e r by t h e f i r i n g o f a p r o d u c t i o n . The PSS c o n d i t i o n ma tche r r e c o g n i z e s a c o n s t r u c t c a l l e d sequence v a r i a b l e s , w h i c h f u l f i l l t h e same f u n c t i o n a s t h e " t h r e e d o t s " o f i n f o r m a l m a t h e m a t i c s ; t h e e x p r e s s i o n " ( A B ) " i n w h i c h i s a sequence v a r i a b l e i s i n t e r p r e t e d a s "any l i s t c o n t a i n i n g A , f o l l o w e d b y any number o f e x p r e s s i o n s , f o l l o w e d b y B " . Sequence v a r i a b l e s match a g a i n s t t h e empty sequence , s o t h a t " ( A B ) " i s a n I n s t a n c e o f " ( A B ) " . A s a n example o f t h e use o f sequence v a r i a b l e s , t h e e x p r e s s i o n " ( X 1 ) " w i l l b i n d t h e v a r i a b l e X 1 t o t h e l a s t e x p r e s s i o n i n any l i s t w h i c h has a t l e a s t one e l e m e n t . As a second e x a m p l e , t h e e x p r e s s i o n "(ALTERNATIVES: X1 )" w i l l r e c o g n i z e a l i s t w i t h one o r more a l t e r n a t i v e s . The sequence v a r i a b l e s a r e bound t o t h e sequences t h e y match a g a i n s t . The PSS sequence v a r i a b l e s can be seen as a deve lopmen t o f t h e " r e m a i n i n g segment " f e a t u r e ( " ! " ) o f t h e OPS language f a m i l y ( F o r g y & M c D e r m o t t , 1 9 7 7 ) . B. The Prob lem S o l v e r The n e x t l a y e r o f UPL i s a t a s k i n d e p e n d e n t , weak p r o b l e m s o l v e r c o n s i s t i n g o f 1 3 nodes w i t h v a r i o u s t a s k s , such a s s e t t i n g g o a l s , m a i n t a i n i n g t h e g o a l s t a c k , g e n e r a t i n g a c t i o n s , c e n s o r i n g a c t i o n s , d o i n g c o n f l i c t r e s o l u t i o n , e x e c u t i n g a c t i o n s , e v a l u a t i n g r e s u l t s o f a c t i o n s , b a c k i n g u p , and r e s t a r t i n g . The p rogram t a k e s a p r o b l e m space and a p r o b l e m as i n p u t . A p r o b l e m space is g i v e n to t h e p rogram in two p a r t s , a BNF grammar d e f i n i n g a k n o w l e d g e s t a t e , and a l i s t o f o p e r a t o r d e f i n i t i o n s . A p r o b l e m i s p r e s e n t e d a s a n o r d e r e d p a i r o f s t a t e s , t h e i n i t i a l s t a t e and t h e g o a l s t a t e . The p r o b l e m s o l v e r i s t a s k i n d e p e n d e n t i n t h e sense t h a t i t does n o t make any a s s u m p t i o n s a b o u t t h e e x p r e s s i o n s w h i c h a r e used a s t h e k n o w l e d g e e l e m e n t s o f t h e p r o b l e m s p a c e .
منابع مشابه
Exploring undergraduate medical students’ perception of learning procedural skills and its outcomes in clinical settings
Introduction: Learning procedural skills is one of the essentialaspects of undergraduate medical education. However, learningprocedural skills in clinical settings is less widely considered.This study aimed to explore the Iranian undergraduate medicalstudents’ perception of learning procedural skills and its outcomesin three universities of medical sciences in Iran...
متن کاملThe Efficacy of Procedural and Declarative Learning Strategies on EFL Students’ Oral Proficiency
Style and strategies in EFL learning contexts and the effects of task types were explored to enhance language learning strategies. Using a quantitative pre-test, post-test design and interviews, this study investigated the effects of procedural and declarative learning strategies on EFL learners’ acquisition of English past tense performing narrative tasks. The participants were 396 male and fe...
متن کاملA Comparison of Expert and Novice Iranian EFL Teachers’ Procedural Knowledge in Iranian Language Institutes and Universities
This study sought to compare Iranian EFL novice and expert teachers regarding their procedural knowledge in Iranian language institutes and universities. A questionnaire was developed based on the literature, the theoretical framework, and the results of a qualitative study. This questionnaire was administered to the whole sample of the study who was 200 Iranian EFL teachers from different gend...
متن کاملExtending the Computational Abilities of the Procedural Learning Mechanism in ACT-R
The existing procedural learning mechanism in ACT-R (Anderson & Lebiere, 1998) has been successful in explaining a wide range of adaptive choice behavior. However, the existing mechanism is inherently limited to learning from binary feedback (i.e. whether a reward is received or not). It is thus difficult to capture choice behavior that is sensitive to both the probabilities of receiving a rewa...
متن کاملEvaluation of procedural learning by medical students of Shiraz University of Medical Sciences according to their logbooks in 2009
This article has no abstract.
متن کاملNeurally-Guided Procedural Models: Learning to Guide Procedural Models with Deep Neural Networks
We present a deep learning approach for speeding up constrained procedural modeling. Probabilistic inference algorithms such as Sequential Monte Carlo (SMC) provide powerful tools for constraining procedural models, but they require many samples to produce desirable results. In this paper, we show how to create procedural models which learn how to satisfy constraints. We augment procedural mode...
متن کامل